Heart rate detection device and operating method thereof, physiological detection device

ABSTRACT

There is provided a heart rate detection device including a sensing unit for sensing emergent light from subcutaneous tissues illuminated by a single light source of multiple light colors to output multiple light detection signals associated with multiple wavelengths. The heart rate detection device further includes a processor uses the multiple light detection signals associated with the multiple wavelengths to cancel motion artifact to obtain a clean heart rate signal.

BACKGROUND 1. Field of the Disclosure

This disclosure generally relates to the physiological detection and,more particularly, to a heart rate detection device capable of removingmotion artifact caused by muscle activities by using light of multiplewavelengths and an operating method thereof.

2. Description of the Related Art

Conventionally, the heart rate detection can be performed by analyzingelectrocardiogram (ECG). However, two electrodes are required to detectthe ECG such that it is not convenient in operation. Therefore, inrecent years an optical type of heart rate detection is used, and anoptical heart rate detector is adaptable to portable and wearableelectronic devices.

It is known that the optical physiological detection can be influencedby the relative movement between a detection device and a skin surface.Especially when an optical detection device is applied to a wearabledevice, a user likes to use the optical detection device to detect theheart rate variation during exercises such that the detection accuracyis degraded due to the influence of noises.

One conventional method to reduce the noises is to operate an opticalphysiological detection device in conjunction with an accelerationdetector. The detection result of the acceleration detector is used todenoise the detection result of the optical physiological detectiondevice so as to increase the detection accuracy. However, this kind ofdenoising method cannot remove noises caused by simple muscleactivities, e.g., a user only moving his/her wrist or finger(s) withoutwaving his/her arm. In this scenario, the acceleration detector is notable to generate usable results for denoising.

In addition, in the conventional physiological detection, the influenceof noises on detection results caused by said simple muscle activitiesis not discussed, and the method of how to remove this motion artifactis not provided.

Accordingly, it is necessary to provide a physiological detection devicecapable of removing the motion artifact caused by muscle activitiesunder a detected skin region so as to improve the detection accuracy.

SUMMARY

The present disclosure provides a heart rate detection device and anoperating method thereof that perform a vector operation between apredetermined intensity distribution of multiple light colors andcurrent light detection signals of the multiple light colors so as toeliminate the motion artifact in detected photoplethysmogram (PPG)signals.

The present disclosure further provides a physiological detection devicewith high detection efficiency and low power consumption.

The present disclosure provides a heart rate detection device includingat least one light source, a light detector and a processor. Each of theat least one light source is configured to emit light covering multiplewavelengths to illuminate a skin surface of a user. The light detectorhas a sensing unit configured to sense emergent light from the skinsurface and output multiple light detection signals associated withdifferent light colors corresponding to the multiple wavelengths. Theprocessor is configured to perform a vector calculation between themultiple light detection signals and a pre-stored intensity distributionof the different light colors to remove a motion artifact.

The present disclosure further provides an operating method of a heartrate detection device. The heart rate detection device includes a lightsource of multiple wavelengths, a light detector and a processor. Theoperating method includes the steps of: entering a register mode, theregister mode including: illuminating, by the light source, a first skinsurface of a user; sensing, by the light detector, emergent light fromthe first skin surface to generate multiple first light detectionsignals associated with different light colors; and calculating andstoring, by the processor, registered data of a plurality of sections ofsample data associated with the different light colors; and entering aworking mode, the working mode including: illuminating, by the lightsource, a second skin surface of a user; sensing, by the light detector,emergent light from the second skin surface to generate multiple secondlight detection signals associated with the different light colors; andperforming, by the processor, a vector calculation between every sectionof sample data of the multiple second light detection signals and theregistered data to remove a motion artifact.

The present disclosure further provides a physiological detection deviceincluding a white light source, a molding and a pixel array. The whitelight source is configured to emit white light having a colortemperature between 2800K and 3200K. The molding is formed upon thewhite light source and configured to constrain an emission angle of thewhite light between 60 and 80 degrees. The pixel array is covered by afilter layer having a passband between 570 nm and 610 nm configured tofilter the white light.

In the embodiments of the present disclosure, the light detector is usedto sense reflected and scattered light from subcutaneous tissuesilluminated by a light source of multiple wavelengths. The light sourceof multiple wavelengths is a white light emitting diode (LED) or whitelight laser diode (LD). Or, the light source of multiple wavelengths isformed by multiple LED dies or multiple LD dies respectively emittinglight of different wavelengths. A distance between different dies ispreferably smaller than 2000 micrometers such that emission lightstherefrom go through substantially identical muscle fibers or bundles.For example, said different dies are formed on the same substrate.

In the embodiments of the present disclosure, it is preferably to use asingle pixel matrix to operate in conjunction with a light source ofmultiple wavelengths. The pixel distance between pixels of said singlepixel matrix is preferably smaller than 2000 micrometers to receiveemergent lights from substantially identical muscle fibers or musclebundles.

In the embodiments of the present disclosure, when the light source ofmultiple wavelengths is a white light source, a pixel array of the lightdetector is covered by a filter layer of multiple colors to achieve thepurpose of detecting light of different colors. If the light source ofmultiple wavelengths is formed by multiple dies for emitting light ofdifferent colors, the pixel array of the light detector is not coveredby a filter layer of different light colors. By lighting the dies toemit light of different colors at different times, the purpose ofdetecting light of different colors is also achievable.

In the embodiments of the present disclosure, at least two lightwavelengths are used, and a wavelength difference between differentlight wavelengths is preferably larger than 25 nm to achieve a betterdenoising effect. However, if only two light wavelengths are used, thewavelength difference should be selected as large as possible, e.g.,preferably larger than 50 nm.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects, advantages, and novel features of the present disclosurewill become more apparent from the following detailed description whentaken in conjunction with the accompanying drawings.

FIG. 1 is a schematic block diagram of a heart rate detection deviceaccording to one embodiment of the present disclosure.

FIG. 2A is a schematic diagram of the arrangement of the light sourceand light detector of a heart rate detection device according to oneembodiment of the present disclosure.

FIG. 2B is a schematic diagram of the arrangement of the light sourceand light detector of a heart rate detection device according to anotherembodiment of the present disclosure.

FIG. 3A is a flow chart of an operating method of a heart rate detectiondevice according to one embodiment of the present disclosure.

FIG. 3B is a schematic diagram of multiple light detection signalsdetected by a heart rate detection device according to one embodiment ofthe present disclosure.

FIG. 4 is a schematic diagram of vector calculated data generated by aheart rate detection device according to one embodiment of the presentdisclosure.

FIG. 5 is a schematic diagram of a white light source and a moldingthereon of a physiological detection device according to one embodimentof the present disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENT

It should be noted that, wherever possible, the same reference numberswill be used throughout the drawings to refer to the same or like parts.

The physiological detection device of the present disclosure is used todetect photoplethysmogram (PPG) signals, and calculate a heart rate andanalyze the user state reflected by a heart rate waveform according tothe PPG signals. In addition to eliminate noises caused by a relativemovement between the device and a detected skin, the physiologicaldetection device of the present disclosure further removes a motionartifact from muscle fibers or muscle bundles under the detected skin(even no relative movement between the device and the detected skin),e.g., caused by activities like typing, rotating wrist, folding fingersand stretching fingers.

Referring to FIG. 1, it is a schematic block diagram of a heart ratedetection device 100 according to one embodiment of the presentdisclosure. The heart rate detection device 100 includes at least onelight source of multiple wavelengths 11, a light detector 13 and aprocessor 15, wherein the light detector 13 and the processor 15 areformed, for example, in the same sensor chip, but not limited to. In onenon-limiting embodiment, the light source 11, the light detector 13 andthe processor 15 are formed in one encapsulation, and embedded in awearable or portable electronic device such as a watch or a cell phone.

The light source 11 includes, for example, a light emitting diode (LED),a laser diode (LD) or the like. The light detector 13 includes, forexample, a CCD image sensor, a CMOS image sensor or the like. Theprocessor 15 includes, for example, a digital signal processor (DSP), amicrocontroller (MCU), a graphic processing unit (GPU), a centralprocessing unit (CPU), an application specific integrated circuit (ASIC)or the like.

Each of the at least one light source 11 emits light covering orcontaining multiple wavelengths (e.g., λ₁, λ₂ . . . λ_(M) shown inFIG. 1) to illuminate a skin surface S of a user, wherein the skinsurface S is determined according to an arranged location of the heartrate detection device 100, e.g., on a forearm or upper arm, withoutparticular limitations. A wavelength range of the multiple wavelengthsis determined according to a number of required wavelengths. Forexample, if a number of detection signals associated with differentlight colors required in calculating a heart rate (illustrated by anexample below) is larger, a wider wavelength range is used. As shown inFIG. 1, although lights of different colors have different penetrationdepths, they still go through at least some identical tissues. Forexample, a wavelength difference between the different light colors isat least 25 nm to allow the detection signals to have enough differencetherebetween.

The light detector 13 includes a sensing unit (e.g., a single pixelarray 131 in FIG. 2A) used to output multiple light detection signalsassociated with different light colors corresponding to the multiplewavelengths, wherein the light detection signals are referred as PPGsignals herein, e.g., FIG. 1 showing light detection signals PPG₁, PPG₂. . . PPG_(M). As body tissues have different absorptivity on differentlight colors, different light detection signals have differentintensities, e.g., referring to FIG. 3B.

Referring to FIGS. 2A and 2B, they are schematic diagrams of arrangingthe light source and the light detector in a heart rate detection deviceaccording to some embodiments of the present disclosure.

In one non-limiting embodiment, the light source 11 is a white lightsource. The single pixel array 131 includes multiple pixel regions,e.g., FIG. 2A showing pixel regions A_(λ1) to A_(λM). The multiple pixelregions A_(λ1) to A_(λM) are covered by a filter layer of differentlight colors (e.g., corresponding to λ₁ to λ_(M)) to allow the multiplepixel regions A_(λ1) to A_(λM) of the single pixel array 131 to outputmultiple detection signals (e.g., PPG₁, PPG₂ . . . PPG_(M) shown inFIG. 1) associated with the different light colors. For example, thepixel region A_(λ1) outputs PPG1, the pixel region A_(λ2) outputs PPG2,and so on.

Each pixel region A_(λ1) to A_(λM) includes one or multiple pixels. Inone non-limiting aspect, each pixel region has a substantially identicalarea and further has a same number of pixels, but not limited thereto.When one pixel region includes multiple pixels, light detection signalsof said multiple pixels are added by a hardware circuit or softwarecodes to output a sum of light detection signals as the light detectionsignals PPG₁, PPG₂ . . . PPG_(M) shown in FIG. 1.

It should be mentioned that although FIG. 2A shows four white lightsources 111-114 each emitting white light on a substrate 10, it is usedto increase the possibility of detecting a motion artifact of muscles bythe light detector 13. The heart rate detection device 100 of thepresent disclosure is for removing noises of tiny activities of musclesunder the detected skin, and muscle bundles that have activities aredetermined according to the type of user's motion, such as fingermovement. In some scenarios, emission light from light sources ofmultiple wavelengths 111 and 113 arranged at two opposite sides along afirst direction of the pixel array 131 of the light detector 13 causethe pixel array 131 to detect a motion artifact but emission light fromlight sources of multiple wavelengths 112 and 114 arranged at twoopposite sides along a second direction of the pixel array 131 of thelight detector 13 do not cause the pixel array 131 to detect the motionartifact, or vice versa. Or emission light from all white light sources111 to 114 can cause the pixel array 131 to detect the motion artifact.

More specifically, if tissues passed by emission light of one whitelight source have activities, the pixel array 131 can detect the motionartifact. Accordingly, employing only one white light source issufficient, and it is not necessary to adopt multiple light sources eachemitting light covering multiple wavelengths. It is also an option toarrange multiple white light sources surrounding the pixel array 131 toincrease the detection possibility. In addition, as identical musclefibers or muscle bundles are within a very small range, a distance Drbetween two adjacent pixel regions A_(λ1) to A_(λM) is preferablysmaller than 2000 micrometers, for example 1500, 1200, 1000, 800 or 600micrometers, to effectively cancel the motion artifact. For example,when different pixel regions A_(λ1) to A_(λM) receive emergent lightfrom different muscle fibers or bundles, the denosing function isdegraded. Therefore, the region distance Dr is not simply a value ofchoice but with its physical meaning.

In another non-limiting embodiment, the pixel array 131′ of the lightdetector 13 is not divided into multiple pixel regions for detectingdifferent light colors as shown in FIG. 2B. The multiple light detectionsignals associated with different light colors are detected bycontrolling the light source of multiple wavelengths to emit light ofdifferent colors at different times. For example, the light source 11includes a single die which is controlled to emit light of differentwavelengths by controlling its driving parameter (e.g., driving voltageor current) or by controlling a variable color filter covering on thesingle die. Or, the light source 11 includes multiple dies (e.g., shownas L_(λ1) to L_(λM) in FIG. 2B) for emitting light containing orcovering multiple wavelengths.

As mentioned above, to sense light from substantially identical musclefibers or bundles, a die distance d_(L) between the multiple dies L_(λ1)to L_(λM) in the light source 11 is preferably smaller than 2000micrometers, e.g., the multiple dies being encapsulated within the samemolding and on the same base layer, to allow the emission lighttherefrom to penetrate substantially identical muscle fibers or bundlesto effectively cancel motion artifact caused by tiny activities.Similarly, the die distance d_(L) is not simply a value of choice butwith its physical meaning. Similarly, the multiple dies shown in FIG. 2Bare selected to be arranged at a single side, two opposites sides orsurrounding the pixel array 131′.

The processor 15 performs a vector calculation between multiple currentlight detection signals (e.g., obtained in a working mode) and apre-stored intensity distribution or ratio of different light colors(e.g., obtained in a register mode) to cancel the motion artifact,wherein the pre-stored intensity distribution or ratio of the differentlight colors is obtained and stored by using the single pixel array 131or 131′ to detect multiple intensities of the multiple light detectionsignals PPG₁, PPG₂ . . . PPG_(M) associated with the different lightcolors when the user is motionless (i.e., muscles under the detectedskin having no activity). That is, the heart rate detection device 100further has a memory (including a volatile memory and/or a non-volatilememory) for storing the intensity distribution or ratio as well as thealgorithm and parameters required for operation.

Referring to FIGS. 3A and 3B, FIG. 3A is a flow chart of an operatingmethod of a heart rate detection device according to one embodiment ofthe present disclosure which is applicable to the heart rate detectiondevice 100 of FIGS. 1-3; and FIG. 3B is a schematic diagram of multiplelight detection signals PPG₁, PPG₂ . . . PPG_(M) (i.e., corresponding toλ₁ to λ_(M)) detected by a heart rate detection device according to oneembodiment of the present disclosure. The operating method of thisembodiment includes the steps of: entering a register mode (Step S31);creating registered data in the register mode (Step S32); entering aworking mode (Step 33); performing a vector calculation between sampledata and the registered data in the working mode (Step S34); andcalculating a heart rate according to the vector calculated data (StepS35).

As mentioned above, the register mode is a detection mode that a user ismotionless, e.g., a steady interval in FIG. 3B. For example, when theuser executes an APP or presses a button on a heart rate detectiondevice 100, the heart rate detection device 100 enters the registermode. Meanwhile, the part of body of the user carrying the heart ratedetection device 100 is completely steady so as to record registereddata associated with different light colors. The registered dataindicates the intensity distribution or ratio of light detection signalsassociated with different light colors when there is no motion artifact.

In the operating method of this embodiment, the working mode is referredto a mode that a user carries the heart rate detection device 100 ineveryday life, e.g., a motion interval shown in FIG. 3B. The workingmode is also entered when, for example, the user executes an APP orpresses a button. If the light detection signals, which are detected inthe working mode and contain the motion artifact, associated withdifferent light colors are projected back to the pre-stored intensitydistribution or ratio, the motion artifact can be removed.

Referring to FIGS. 1 and 3A-3B, details of FIG. 3A are described usingan example below. The processor includes, for example, a normalizer, afilter and an intensity calculator.

Steps S31-S32: In the register mode, the processor 15 controls the lightsource 11 to illuminate a first skin surface of a user. Meanwhile, thepixel array 131 or 131′ of the light detector 13 senses emergent lightfrom the first skin surface to generate multiple first light detectionsignals associated with different light colors, e.g., PPG₁, PPG₂ . . .PPG_(M) shown in FIG. 3B, wherein the light detector 13 acquires aplurality of sections of sample data associated with different lightcolors (illustrated by an example below) at a fixed or adjustablesampling frequency. The processor 15 then uses the plurality of sectionsof sample data associated with different light colors to calculate andstore registered data, which reflects the intensity distribution orratio of light of different colors.

For example, the processor 15 continuously receives the multiple firstlight detection signals PPG₁, PPG₂ . . . PPG_(M) associated withdifferent light colors. In the present disclosure, each light detectionsignal among the multiple light detection signals detected by the lightdetector 13 is referred to one channel, and each channel is associatedwith one of the multiple different light colors. The processor 15samples, within each sampling interval, a predetermined number of samplepoints (e.g., L points herein) each at a different time of every channelof the multiple first light detection signals PPG₁, PPG₂ . . . PPG_(M)as one section of sample data. It is appreciated that a light wavelengthrange of one channel herein includes not only a single wavelength butmultiple wavelengths within a predetermined light wavelength range,e.g., full width at half maximum (FWHM).

For example, the L sample points of all M channels within one samplinginterval acquired by the processor 15 are indicated by an M×L matrix asone section of sample data. As time goes by, the processor 15 acquiresone M×L matrix within every sampling interval, and thus the processor 15acquires a plurality of sections of sample data from every channel ofthe multiple first light detection signals PPG₁, PPG₂ . . . PPG_(M)associated with different light colors within a register interval (i.e.one register interval including a plurality of sampling intervals) toobtain a plurality of M×L matrices.

Next, the normalizer of the processor 15 normalizes every section ofsample data (i.e. each M×L matrix) of the plurality of sections ofsample data (i.e. the plurality of M×L matrices) of the multiple firstlight detection signals. For example, the normalization is to remove thedc component from each sampled value.

After the normalization, the processor 15 selects to filter each sectionof the normalized sample data. For example, the filter of the processor15 uses a digital filter having a passband between 0.5 Hz and 3.5 Hz tofilter each section of the normalized sample values.

Then, the intensity calculator of the processor 15 calculates an averageof a standard deviation of the plurality of sections of sample data(e.g., 20 sections of sample data being acquired per second, and thus600 sections being acquired for 30 seconds, but not limited to) of everychannel within a register interval (a predetermined time interval, forexample 30 seconds, but not limited to). Firstly, the processor 15calculates a standard deviation of every section of sample data withinthe register interval. Then, the processor 15 calculates an average ofthe plurality of standard deviations of the plurality of sections ofsample data of each channel.

Finally, the processor 15 obtains the intensity distribution of thecalculated average values of every channel (e.g., PPG1-PPG8 herein),which is used as the registered data associated with different lightcolors.

The processor further includes a vector calculator operates in theworking mode.

Steps S33-S34: In the working mode, the processor 15 controls the lightsource 11 to illuminate a second skin surface of the user, wherein thesecond skin surface is identical to or different from the first skinsurface. Meanwhile, the pixel array 131 or 131′ of the light detector 13senses emergent light from the second skin surface to generate multiplesecond light detection signals associated with different light colors,e.g., PPG₁, PPG₂ . . . PPG_(M) as shown in FIG. 3B. It should bementioned that methods of the pixel array 131 or 131′ of the lightdetector 13 for acquiring the multiple first light detection signals andthe second light detection signals are identical only they are acquiredin different modes (or referred to different stages or different timeintervals).

Similarly, the processor 15 samples, within each sampling interval, apredetermined number of sample points (e.g., L points herein) each at adifferent time of every channel of the multiple second light detectionsignals PPG₁, PPG₂ . . . PPG_(M) as one section of sample data. Forexample, the processor 15 also acquires one M×L matrix for each samplinginterval, wherein the method of the processor 15 for acquiring the M×Lmatrix has been mentioned above, and thus details thereof are notrepeated herein.

The normalizer of the processor 15 normalizes every section of sampledata (i.e. every M×L matrix) of the multiple second light detectionsignals PPG₁, PPG₂ . . . PPG_(M), and then the filter of the processor15 filters every section of the normalized sample data, wherein thenormalizing and the filtering are identical to those mentioned above andthus details thereof are not repeated herein. It should be mentionedthat the filters herein are used for improving the calculation accuracy,but the filters are not necessary to be implemented.

Next, the vector calculator of the processor 15 performs a vectorcalculation between every section of sample data (i.e. R_(M×L)) of themultiple second light detection signals and the registered data tocancel the motion artifact. For example, P is vector calculated data. Inthe working mode, the processor 15 outputs one set of heart rate data P,e.g., P1, P2, P3 . . . as shown in FIG. 4, every one sampling interval,wherein the motion artifact no longer exists in the vector calculateddata P. FIG. 4 shows the processor 15 outputs a plurality of vectorcalculated data P at continuous times (shown by n=0, 1, 2 . . . ). Adata number of each data set P is identical to a sampling number Lwithin each sampling interval acquired by the processor 15.

In the present disclosure, the processor 15 samples a plurality ofsections of sample data (i.e. a plurality of M×L matrices) in theregister mode for creating the registered data, but samples one sectionof sample data (i.e. one M×L matrix) every sampling period in theworking mode for the vector calculation with the registered data.

It is appreciated that channel numbers M of the multiple first detectionsignals and the multiple second detection signals are identical so as toperform the vector calculation. In one non-limiting embodiment, in theregister mode the processor 15 uses more channels (e.g., 8 channelscorresponding to 8 light colors 430 nm, 460 nm, 490 nm, 515 nm, 560 nm,615 nm, 660 nm and 695 nm, but not limited to) to construct theregistered data, and less channels are used in the working mode (e.g., 3channels corresponding to 3 light colors 430 nm, 560 nm and 695 nm, butnot limited to). The processor 15 only reads required data from thememory 17 during accessing the registered data. For example, in theworking mode, when the detection result calculated by using one group ofchannels is not correct, e.g., noises still too high, another group ofchannels are used, by increasing, decreasing or maintaining the channelnumber. In other embodiments, channels among the multiple channels to beused are selected according to a ratio between the AC value and DC valueof a PPG signal (referred as PI value herein), wherein a higher PI valueindicates that a tissue response to the emission light is better. Forexample, a channel having a highest PI value is used in conjunction withthe channel having a lowest PI value for the denoising process.

Finally, in the working mode, the processor 15 calculates a heart rateusing the vector calculated data P in the time domain or frequencydomain. For example, the processor 15 calculates the heart rateaccording to a time interval between two adjacent peaks or othercorresponding kink points in the vector calculated data P, or theprocessor 15 converts the vector calculated data P into the frequencydomain at first and then calculates the heart rate accordingly.

In one non-limiting embodiment, as the sampling frequency (or framerate) of the light detector 13 is higher than the heart rate, toincrease the signal intensity, the processor 15 further adds or overlapsa predetermined number of vector calculated data P or the vectorcalculated data P within a predetermined interval at first (e.g.,P1+P2+P3+ . . . in a section by section manner), and then calculates aheart rate according to a sum of or the overlapped vector calculateddata P.

It should be mentioned that although the above operating method isillustrated in a way that multiple functional blocks are used to performdifferent functions, functions performed by every functional block areconsidered to be performed by the processor 15 using software codesand/or hardware codes.

As mentioned above, the registered data is the intensity distribution orratio of light detection signals associated with every light colorwithout the motion artifact (e.g., the steady interval shown in FIG.3B). In actual operation if the user has some activities (e.g., themotion interval shown in FIG. 3B), the data intensity in the samplingmatrix R_(M×L) of the second light detection signals is influenced bythe noise to deviate from the pre-stored intensity distribution orratio. The vector calculation of the present disclosure is to causeintensities of different light colors of the sampling matrix R_(M×L) tobe projected to the pre-stored intensity distribution or ratio to removethe motion artifact.

In one non-limiting embodiment, the heart rate detection device of thepresent disclosure further includes a display (not shown) for showingthe value and/or waveform of the heart rate.

It should be mentioned that the operating method of FIG. 3A mentionedabove is only one embodiment applicable to the heart rate detectiondevice 100, but not used to limit the present disclosure. The heart ratedetection device 100 may use other algorithms to cancel noises as longas the light detector 13 detects emergent light from substantiallyidentical muscle fibers or bundles, e.g., subtracting multiple lightdetection signals associated with different light colors from each otherto remove the motion artifact.

It is appreciated that values mentioned in the above embodiments, suchas light wavelengths, a number of light sources, a number of sampledpoints, a number of channels, are only intended to illustrate but not tolimit the present disclosure.

A person skilled in the art would know that using white light has a poorefficiency, and thus a white light source is not applied to thephysiological detection system. Meanwhile, according to thecharacteristics of luminescence materials, a monochromatic LED foremitting yellow light between 570 nm and 620 nm does not have highemission efficiency (i.e. consuming more power). Accordingly, although aPPG signal response (i.e. the above PI value) to light between 570 nmand 620 nm is better than to green light, the PI value is sacrificed anda green light source having better emission efficiency is selected toprevent using a yellow light source due to its high power consumption.To increase the PI value and reduce the power consumption (i.e. achievehigh emission efficiency) at the same time, in one embodiment of thepresent disclosure, a white light source having a color temperaturebetween 2800K and 3200K is used. Meanwhile, a filter layer having a passband between 570 nm and 620 nm is covered on a pixel array of the lightdetector for filtering white light emitted by the white light source. Inthis way, the purposes of high PI value and low power consumption areachieved at the same time. For example, for detecting same PI values,using a white LED having a color temperature between 2800K and 3200K canhave about three times of the emission efficiency than using the greenLED or yellow LED. A significant improvement is achieved.

In addition, an optical component is not used to constrain an emissionangle of a white LED because the use purpose of the white LED is forspace illumination such that a wide emission angle is required. Pleasereferring to FIG. 5, to further improve the detection efficiency, aplastic or glass molding 71 is further formed on the white LED to covera die 73 which is arranged on a base layer 75 of the white LED toconstrain an emission angle θ of the white LED to be within 60 and 80degrees to improve the system efficiency.

As mentioned above, the conventional physiological detection device canonly cancel noises caused by stronger exercises but is not able toeliminate motion artifact caused by tiny muscle activities (e.g., thoseundetectable by an acceleration detector). Accordingly, the presentdisclosure further provides a heart rate detection device (e.g., FIGS. 1and 2A-2B) and an operating method thereof (e.g., FIG. 3A) that use asingle pixel array to detect reflected and scattered light fromsubcutaneous tissues illuminated by a light source, which emits lightcovering multiple wavelengths, to generate multiple light detectionsignals associated with different wavelengths. Based on an assumptionthat muscle activities have substantially identical influences on lightdetection signals of every light wavelength, the present disclosurecancel the motion artifact between light detection signals of differentlight wavelengths by, for example calculating the subtractiontherebetween or vector projection, to obtain a clean heart ratewaveform. This clear heart rate waveform can be used to calculate morecorrect heart rates.

Although the disclosure has been explained in relation to its preferredembodiment, it is not used to limit the disclosure. It is to beunderstood that many other possible modifications and variations can bemade by those skilled in the art without departing from the spirit andscope of the disclosure as hereinafter claimed.

What is claimed is:
 1. An operating method of a heart rate detectiondevice, the heart rate detection device comprising a light source ofmultiple wavelengths, a light detector and a processor, the operatingmethod comprising: entering a register mode, the register modecomprising: illuminating, by the light source, a first skin surface of auser; sensing, by the light detector, emergent light from the first skinsurface to generate multiple first light detection signals associatedwith different light colors; and calculating and storing, by theprocessor, registered data of a plurality of sections of sample dataassociated with the different light colors; and entering a working mode,the working mode comprising: illuminating, by the light source, a secondskin surface of the user; sensing, by the light detector, emergent lightfrom the second skin surface to generate multiple second light detectionsignals associated with the different light colors; and performing, bythe processor, a vector calculation between every section of sample dataof the multiple second light detection signals and the registered datato remove a motion artifact.
 2. The operating method as claimed in claim1, wherein calculating the registered data comprises: sampling, by theprocessor within a register interval, the plurality of sections ofsample data on every channel of the multiple first light detectionsignals associated with the different light colors; calculating, by theprocessor, an average of a standard deviation of the plurality ofsections of sample data of every channel within the register interval;and taking multiple average values of different channels as theregistered data associated with the different light colors.
 3. Theoperating method as claimed in claim 2, wherein before calculating theaverage of the standard deviation further comprises: normalizing, by theprocessor, each section of sample data of the plurality of sections ofsample data of the multiple first light detection signals; andfiltering, by the processor, each section of the normalized sample data.4. The operating method as claimed in claim 1, wherein performing thevector calculation further comprises: calculating, by the processor, acovariance matrix of the every section of sample data of the multiplesecond light detection signals; and performing, by the processor, amultiplication on a transfer matrix of the registered data, a reciprocalof the covariance matrix and the every section of sample data of themultiple second light detection signals.
 5. The operating method asclaimed in claim 4, wherein before performing the vector calculationfurther comprises: normalizing, by the processor, the every section ofsample data of the multiple second light detection signals; andfiltering, by the processor, each section of the normalized sample data.6. The operating method as claimed in claim 1, wherein a channel numberof the multiple first light detection signals is identical to that ofthe multiple second light detection signals, and each channel isassociated with one of the different light colors.
 7. The operatingmethod as claimed in claim 6, wherein the processor samples, within eachsampling interval, a predetermined number of sample points each at adifferent time of the each channel of the multiple first light detectionsignals and the multiple second light detection signals as one sectionof sample data.
 8. The operating method as claimed in claim 1, furthercomprising: adding, by the processor in the working mode, the vectorcalculated data associated with a plurality of sections of sample dataof the multiple second light detection signals.
 9. The operating methodas claimed in claim 1, further comprising: calculating, by the processorin the working mode, a heart rate in time domain or frequency domainusing the vector calculation associated with a plurality of sections ofsample data of the multiple second light detection signals.
 10. Theoperating method as claimed in claim 1, wherein the register mode is adetection mode during which the user is motionless.